PO.CH01.02 · 化学
从高度多样化的CRBN分子胶文库中鉴定新型CRBN分子胶三元结合物
Identification of novel CRBN molecular glue ternary binders from a highly diverse CRBN MG library
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
针对cereblon（CRBN）分子胶（MG）偏向性文库的高通量筛选（HTS）仍然是概念验证研究和针对新兴靶标进行苗头化合物鉴定的关键策略。由于CRBN结合口袋及其诱导的界面可以采用多种构象，且底物结合口袋在发现的早期阶段往往难以预测，因此CRBN结合物和底物识别基序的结构多样性对筛选效率至关重要。在这项工作中，我们构建了一个高质量的CRBN MG偏向性文库，源自40多种经过验证的CRBN结合物。为进一步增强化学多样性，我们使用定制的基于AI的分子生成模型引入了新型片段，旨在最大化底物结合基序的变异。HTS案例研究表明，该文库有效地鉴定出具有独特支架的CRBN-底物三元结合物和降解剂，代表了进一步优化的有前景的起点。
查看英文原文 English abstract
High-throughput screening (HTS) of cereblon (CRBN) molecular glue (MG)-biased libraries remains a key strategy for proof-of-concept studies and hit identification against emerging targets. Because the CRBN binding pocket and its induced interface can adopt multiple conformations, and the substrate binding pocket is often unpredictable at the early stages of discovery, the structural diversity of both CRBN binders and substrate-recognition motifs is crucial to screening efficiency.In this work, we constructed a high-quality, CRBN MG-biased library derived from more than 40 validated CRBN binders. To further enhance chemical diversity, we introduced novel fragments using a tailored AI-based molecular generation model, designed to maximize variations in substrate-binding motifs. HTS case studies demonstrated that this library effectively identified CRBN-substrate ternary binders and degraders with unique scaffolds, representing promising starting points for further optimization.
利益披露 Disclosure
Q. Xu, None..
H. Yang, None..
Y. Wang, None..
Z. Wu, None..
H. Zhang, None.